A vehicle hitching assistance system includes a controller executing an initial alignment process including searching for a trailer within a specified area of image data that is less than a total field of the image data in directions corresponding with both a longitudinal distance between the vehicle and the trailer and a lateral direction perpendicular to the longitudinal distance, presenting an indication to a driver of the vehicle to reposition the vehicle when the trailer is not identified within the specified area, and removing the indication when the trailer is identified within the specified area. The controller further executes an automated backing process upon identifying the trailer within the specified area, including identifying a coupler of the trailer and outputting a steering signal to the vehicle to cause the vehicle to steer to align a hitch ball of the vehicle with the coupler of the trailer during reversing.
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2. The system of claim 1, wherein the controller acquires the image data from an imaging system included with the vehicle, the imaging system having at least one camera, the total field of the image data corresponding with a total field of view of the at least one camera.
This invention relates to a vehicle-based imaging system for capturing and processing image data. The system includes a controller and an imaging system mounted on the vehicle, which comprises at least one camera. The imaging system captures image data corresponding to the total field of view of the camera(s). The controller processes this image data to detect and analyze objects or features within the captured images. The system may be used for applications such as obstacle detection, lane tracking, or environmental monitoring. The imaging system provides real-time or near-real-time data to the controller, which may then generate outputs such as alerts, control signals, or data for further processing. The invention improves vehicle safety and autonomy by enhancing situational awareness through comprehensive image capture and analysis. The system may integrate with other vehicle systems, such as navigation or driver assistance modules, to provide a more robust and responsive driving environment. The use of a vehicle-mounted camera ensures that the imaging data is directly relevant to the vehicle's immediate surroundings, reducing latency and improving accuracy in dynamic driving conditions.
4. The system of claim 1, wherein the preselected area of the image data is a circular target area disposed at a preselected location in a central portion of the image data.
This invention relates to image processing systems designed to analyze specific regions within image data. The system focuses on a preselected circular target area located in the central portion of the image data. The circular target area is defined by a predetermined size and position, ensuring consistent analysis of a standardized region. The system processes the image data to extract features or perform measurements within this defined circular area, which may be used for quality control, object detection, or other analytical purposes. The circular shape and central positioning of the target area allow for uniform and repeatable analysis, reducing variability in results. The system may include additional components to capture, preprocess, or enhance the image data before analysis, ensuring the target area is accurately identified and processed. This approach is particularly useful in applications requiring precise and consistent evaluation of a specific region within an image, such as in manufacturing inspection, medical imaging, or automated visual analysis. The invention improves upon existing methods by standardizing the analysis region, thereby enhancing accuracy and reliability in image-based assessments.
5. The system of claim 1, wherein the preselected area within the image data is defined by a designated boundary comprising respective portions based on the maximum detection distance, the minimum detection distance, and the known steering limit of the vehicle.
This invention relates to a vehicle-based detection system designed to monitor and analyze a preselected area within image data captured by one or more sensors. The system addresses the challenge of accurately detecting and tracking objects within a dynamically defined region of interest, particularly in automotive applications where environmental conditions and vehicle movement can vary. The system includes a sensor configured to capture image data of the surrounding environment and a processor that processes this data to identify objects within a preselected area. The preselected area is dynamically defined by a designated boundary, which is determined based on three key parameters: the maximum detection distance, the minimum detection distance, and the known steering limit of the vehicle. The maximum detection distance represents the farthest point at which the system can reliably detect objects, while the minimum detection distance defines the closest point within the detection range. The known steering limit accounts for the vehicle's maneuverability, ensuring the boundary adapts to the vehicle's turning capabilities. By incorporating these parameters, the system dynamically adjusts the boundary of the preselected area to optimize object detection and tracking, improving safety and situational awareness for the vehicle. The processor further analyzes the detected objects within this boundary to generate relevant outputs, such as alerts or control signals for autonomous driving systems. This approach enhances the system's ability to focus on critical regions while minimizing false detections and computational overhead.
6. The system of claim 5, wherein the respective portions of the designated boundary are based on a correlation of the total field of the image data with an area of an assumed ground plane on which the vehicle is positioned visible within the total field.
This invention relates to a system for processing image data captured by a vehicle-mounted camera to determine a designated boundary within the image. The system addresses the challenge of accurately identifying ground plane regions in images where the vehicle is positioned, which is critical for applications such as autonomous navigation, obstacle detection, and environmental mapping. The system correlates the total field of the image data with an assumed ground plane area visible within the image to define respective portions of the boundary. This correlation involves analyzing the image to distinguish between ground and non-ground regions, ensuring that the boundary accurately represents the ground plane on which the vehicle operates. The system may also include a camera configured to capture the image data and a processor to execute the correlation and boundary determination. The boundary is dynamically adjusted based on the correlation results, improving the system's adaptability to varying environmental conditions. This approach enhances the reliability of ground plane detection, which is essential for safe and efficient vehicle operation in autonomous or assisted driving scenarios.
9. The system of claim 8, wherein the controller begins executing the initial alignment process, including outputting the graphic overlay and message in the video image, upon activation of the system.
A system for aligning a graphic overlay with a video image includes a controller that initiates an initial alignment process upon system activation. The process involves generating a graphic overlay and a message, which are then displayed within the video image. The graphic overlay is positioned relative to the video image to ensure proper alignment. The system may also include a camera for capturing the video image and a display for presenting the combined video image and graphic overlay. The controller adjusts the position of the graphic overlay based on input from a user or an automated alignment algorithm to achieve accurate alignment. The initial alignment process ensures that the graphic overlay is correctly positioned when the system is first activated, providing a reference point for further adjustments. This system is useful in applications where precise alignment of graphical elements with video content is required, such as augmented reality, medical imaging, or industrial inspection. The automatic initiation of the alignment process upon activation streamlines the setup and ensures consistent performance.
13. The vehicle of claim 12, wherein after identifying the trailer within a predetermined area of the image data, the controller identifies the coupler of the trailer during execution of the automated backing process.
This invention relates to automated vehicle systems for backing a vehicle while towing a trailer. The problem addressed is the difficulty in accurately detecting and aligning a trailer coupler during automated backing maneuvers, which can lead to misalignment, collisions, or failed coupling attempts. The system includes a vehicle equipped with sensors, such as cameras, to capture image data of the surrounding environment. A controller processes this data to identify the trailer within a predetermined area of the image data. Once the trailer is detected, the controller further analyzes the image data to locate the trailer coupler. This identification occurs during the automated backing process, allowing the system to adjust the vehicle's path in real-time to ensure proper alignment with the trailer coupler. The system may also incorporate additional sensors, such as ultrasonic or radar sensors, to enhance detection accuracy. The invention improves the reliability and precision of automated trailer coupling by dynamically tracking the coupler's position during the backing maneuver, reducing the risk of errors and improving user experience.
14. The vehicle of claim 12, wherein the predetermined area of the image data is within a designated boundary comprising respective portions based on a resolution of the image data, a proportion of the trailer relative to the total field, and a known steering limit of the vehicle.
This invention relates to a vehicle equipped with a camera system for capturing image data of a trailer being towed. The system processes the image data to determine the trailer's position relative to the vehicle, ensuring safe and accurate towing. A key challenge addressed is accurately defining a predetermined area within the image data to analyze the trailer's position, especially under varying conditions such as different image resolutions, trailer sizes, and vehicle steering limits. The vehicle includes a camera configured to capture image data of the trailer, and a processor that analyzes this data to identify the trailer's position. The processor defines a designated boundary within the image data to focus the analysis on the relevant portion. This boundary is dynamically adjusted based on the resolution of the image data, the proportion of the trailer relative to the total field of view, and the known steering limit of the vehicle. By accounting for these factors, the system ensures that the analysis remains precise and reliable, even when conditions change. This approach improves towing safety by providing accurate positional feedback to the driver or an automated control system.
15. The vehicle of claim 14, wherein the respective portions of the designated boundary are based on a correlation of the total field of the image data with an area of an assumed ground plane on which the vehicle is positioned visible within the total field.
This invention relates to vehicle imaging systems, specifically for determining a designated boundary within image data captured by a vehicle-mounted camera. The problem addressed is accurately defining a relevant region of interest in the image data, particularly for applications like autonomous driving or advanced driver assistance systems, where distinguishing between relevant and irrelevant portions of the scene is critical. The system involves a vehicle equipped with a camera that captures image data of the surrounding environment. The designated boundary within the image data is determined by correlating the total field of the image with an assumed ground plane on which the vehicle is positioned. The ground plane represents the visible portion of the road or surface directly in front of the vehicle, which is a key area for navigation and obstacle detection. By analyzing the correlation between the image data and this ground plane, the system identifies specific portions of the image that correspond to the relevant boundary. This boundary may be used to focus processing resources on the most critical areas of the image, improving efficiency and accuracy in tasks such as object detection, lane tracking, or path planning. The correlation process involves comparing the image data to the expected characteristics of the ground plane, such as perspective distortion or texture patterns, to dynamically adjust the boundary based on real-time conditions. This ensures that the designated boundary adapts to changes in the environment, such as road curvature or obstacles, while maintaining focus on the most relevant portions of the scene. The system may also incorporate additional sensors or data sources to refine the boundary determination, enhancing overall reliability.
16. The vehicle of claim 12, wherein the controller further indicates to a driver of the vehicle to reposition the vehicle until the trailer is identified within the predetermined area.
A system for assisting in trailer coupling involves a vehicle equipped with sensors and a controller. The sensors detect the position of a trailer relative to the vehicle's hitch. The controller determines whether the trailer is within a predefined coupling area, which is a spatial region where the trailer can be successfully connected to the vehicle's hitch. If the trailer is outside this area, the controller provides feedback to the driver, such as visual or audible alerts, to guide the vehicle's repositioning. The feedback may include directional instructions to adjust the vehicle's position until the trailer is correctly aligned within the coupling area. The system ensures precise alignment before coupling, reducing the risk of misalignment or damage. The sensors may include cameras, ultrasonic sensors, or other detection methods to monitor the trailer's position in real time. The controller processes the sensor data to calculate the trailer's position and compares it to the predefined coupling area. The system may also include a user interface to display alignment status and guidance instructions. This technology addresses the challenge of accurately aligning a trailer with a vehicle's hitch, improving efficiency and safety during the coupling process.
18. The method of claim 17, wherein the preselected area of the image data is within a designated boundary comprising respective portions based on a resolution of the image data, a proportion of the trailer relative to the total field, and a known steering limit of the vehicle.
This invention relates to image processing for vehicle systems, specifically for analyzing image data to determine a preselected area of interest within a captured image. The technology addresses the challenge of efficiently identifying and focusing on relevant portions of an image, such as those containing a trailer or other objects, while accounting for varying image resolutions, field proportions, and vehicle steering constraints. The method involves defining a designated boundary within the image data, where the boundary is dynamically adjusted based on multiple factors. These factors include the resolution of the image data, the proportion of the trailer relative to the total field of view, and the known steering limit of the vehicle. By incorporating these parameters, the system ensures that the preselected area accurately captures the relevant portion of the image while minimizing unnecessary processing of irrelevant regions. This approach optimizes computational efficiency and improves the accuracy of subsequent analysis, such as object detection or tracking. The designated boundary is divided into portions that adapt to the image resolution, ensuring that the preselected area scales appropriately regardless of the image's pixel density. The proportion of the trailer relative to the total field is used to dynamically adjust the boundary's size and position, ensuring that the trailer remains within the preselected area even as the vehicle maneuvers. Additionally, the known steering limit of the vehicle is factored in to prevent the boundary from extending beyond physically possible steering angles, further refining the area of interest. This method enhances the reliability of image-based systems in vehicle applications.
19. The method of claim 18, wherein the respective portions of the designated boundary are based on a correlation of the total field of the image data with an area of an assumed ground plane on which the vehicle is positioned visible within the total field.
This invention relates to a method for determining a designated boundary within image data captured by a vehicle-mounted imaging system. The method addresses the challenge of accurately identifying a ground plane boundary in an image, which is essential for applications such as autonomous navigation, obstacle detection, and environmental mapping. The method involves analyzing the total field of the image data to correlate it with an assumed ground plane visible within the image. By comparing the image data to the expected characteristics of the ground plane, the method determines respective portions of the designated boundary. This correlation helps distinguish the ground plane from other objects or surfaces in the image, ensuring accurate boundary detection. The method may also involve preprocessing the image data, such as filtering or enhancing specific features, to improve the correlation process. The resulting boundary can be used to define a region of interest for further analysis or to guide vehicle navigation decisions. The invention enhances the reliability of ground plane detection in dynamic environments, reducing errors caused by varying lighting conditions, occlusions, or complex terrain.
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September 22, 2022
April 23, 2024
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